The goal of this work is to identify electrostatic features of toxin structures that control their relative binding affinities for the large- conductance, calcium-activated potassium (maxi-K) channel. These channels have been identified as therapeutic targets for diseases such as hypertension, asthma, and diseases associated with memory and learning. Peptide toxins that specifically bind to and interfere with maxi-K channel function are critical to their development as therapeutic targets for disease. Site specific mutants of low and high affinity blockers of the maxi-K channel will be generated to determine how electrostatic features control the rates of toxin association and dissociation. We will identify charged toxin residues that confer specificity through intimate toxin- channel contacts and quantitate the specific contribution of each contact to the dissociation rate. We will employ a model where toxin dissociation requires the disruption of all toxin-channel contacts, and the transition free energy for dissociation reports the sum of each contact. We will test whether low (NxTX) and high (IbTX and ThTX(Q1V)) affinity blockers and their site-directed mutants share similar macroscopic and microscopic binding sites in the extracellular mouth of the maxi-K channel. Additivity of the transition free energy of dissociation will be used to test for interactions between residues. Electrostatic diversity in the toxin isomers is manifested in striking differences in their distributions of charge. To determine how these differences control toxin association rates and specificity, we will generate site-directed mutants of ThTX, IbTX(Q1V) and NxTX that distinguish between the effects of net charge and charge asymmetry. We will also test whether long- or short- range electrostatic attraction controls toxin association rates. Electrostatic calculations of the 3-D structure of IbTX and models of NxTX will guide the rational design of site-directed mutants. From these results, we will develop and test a model of electrostatic features that control specific high affinity interactions with the maxi-K channel. These results will provide tremendous insight into our understanding of the types of electrostatic interactions that control toxin specificity. They will also further our understanding of how electrostatic forces control protein-protein interactions and molecular recognition.